total_images = nb_images_to_show * len(panels.keys())
fig, ax = plt.subplots(2*total_images, 3,
figsize=(12, 8*total_images))
for i, panel_name in enumerate(panel_names):
# List masks and images
masks_subdir = folders["masks_cells"] / panel_name / segmentation_type
seg_subdir = folders["seg_cells"] / panel_name
masks = io.list_mask_files(masks_subdir)
for j in range(nb_images_to_show):
k = 2 * (j + (i * nb_images_to_show))
# Load random images and masks, create an overlay
rng = np.random.default_rng()
ix = rng.choice(len(masks))
cur_filename = masks[ix].name
img = io.read_image(seg_subdir / cur_filename)
cur_img = (img / np.amax(img))[0,...]
mask = io.read_image(masks_subdir / cur_filename)
cur_mask = mask[0,...].astype('uint16')
# print(cur_img.shape, cur_mask.shape)
# Overlay image and cell labels
cur_img = exposure.adjust_sigmoid(cur_img, 0.1)
cur_img = color.gray2rgb(cur_img)[...,0]
overlay1 = color.label2rgb(cur_mask, cur_img,
alpha = overlay_alpha, bg_label=0)
# Overlay image and mask borders
borders = mark_boundaries(cur_img, cur_mask, mode = "thin")[...,0]
overlay2 = addWeighted(cur_img*255, 1, borders*65535, 1, 0)
# Display images and masks
ax[k,0].imshow(img[0,:,:], vmax = max_intensity)
ax[k,0].set_title(cur_filename)
ax[k,1].imshow(overlay1, cmap = cmap)
ax[k,1].set_title("Overlay")
ax[k,1].axis('off')
ax[k,2].imshow(overlay2)
ax[k,2].set_title("Borders")
ax[k,2].axis('off')
# Higher magnification (change coordinates and dimensions if needed)
xstart = 100
ystart = 100
dim = 100
ax[k+1,0].imshow(img[0,:,:], vmin = 0, vmax = max_intensity)
ax[k+1,0].set_xlim([xstart, xstart + dim])
ax[k+1,0].set_ylim([ystart, ystart + dim])
ax[k+1,1].imshow(overlay1, cmap = cmap)
ax[k+1,1].set_xlim([xstart, xstart + dim])
ax[k+1,1].set_ylim([ystart, ystart + dim])
ax[k+1,1].axis('off')
ax[k+1,2].imshow(overlay2)
ax[k+1,2].set_xlim([xstart, xstart + dim])
ax[k+1,2].set_ylim([ystart, ystart + dim])
ax[k+1,2].axis('off')
# Save the overlay
if save_overlay:
overlay_dir = folders["masks_cells"] / panel_name / "overlay"
overlay_dir.mkdir(exist_ok = True)
overlay_file = overlay_dir / masks[ix].name
io.write_image(np.moveaxis(overlay1, -1, 0), overlay_file)
